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1
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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2
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
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3
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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4
Intrinsic Probing through Dimension Selection ...
Abstract: Most modern NLP systems make use of pre-trained contextual representations that attain astonishingly high performance on a variety of tasks. Such high performance should not be possible unless some form of linguistic structure inheres in these representations, and a wealth of research has sprung up on probing for it. In this paper, we draw a distinction between intrinsic probing, which examines how linguistic information is structured within a representation, and the extrinsic probing popular in prior work, which only argues for the presence of such information by showing that it can be successfully extracted. To enable intrinsic probing, we propose a novel framework based on a decomposable multivariate Gaussian probe that allows us to determine whether the linguistic information in word embeddings is dispersed or focal. We then probe fastText and BERT for various morphosyntactic attributes across 36 languages. We find that most attributes are reliably encoded by only a few neurons, with fastText ... : To appear EMNLP 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2010.02812
https://arxiv.org/abs/2010.02812
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5
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
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6
The Paradigm Discovery Problem ...
Erdmann, Alexander; Elsner, Micha; Wu, Shijie. - : ETH Zurich, 2020
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7
Information-Theoretic Probing for Linguistic Structure ...
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8
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ...
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9
Information-Theoretic Probing for Linguistic Structure ...
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10
Intrinsic Probing through Dimension Selection ...
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11
Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ...
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12
A Corpus for Large-Scale Phonetic Typology ...
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13
Phonotactic Complexity and its Trade-offs ...
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14
Phonotactic Complexity and Its Trade-offs ...
Pimentel, Tiago; Roark, Brian; Cotterell, Ryan. - : ETH Zurich, 2020
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15
A Corpus for Large-Scale Phonetic Typology ...
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16
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
Leung, Jun Yen; Emerson, Guy; Cotterell, Ryan. - : ETH Zurich, 2020
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17
Morphologically Aware Word-Level Translation ...
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18
Predicting Declension Class from Form and Meaning ...
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19
Predicting declension class from form and meaning
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20
Please Mind the Root: Decoding Arborescences for Dependency Parsing
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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